1. Field of the Invention
The present invention relates to a time factor feature generation system that analyses a time factor feature of a use status of a site such as, for example, a Web site providing a service such as e-banking, e-commerce or the like, a method of the analysis, and a program for the analysis.
2. Description of Related Art
For example, services such as e-banking, e-commerce and the like have been provided on Web sites on a computer network. Further, with an expectation of encouraging service users to use, sign contracts for, or purchase particular services, service providers deliver or present various electronic advertisements to the users through a network.
In presenting an electronic advertisement, it is possible to arbitrarily change a time period and a location for the presentation. Further, it is possible to estimate a reaction characteristic of uses with respect to the electronic advertisement based on, for example, log data of a service-providing site on the Web.
In recent years, advancement of IT technologies (for example, widespread use of mobile equipment/sensor actuators) has allowed services and electronic advertisements to be controlled finely so as to be suitable for the respective scenes of use by individual users. It has thus been requested that a method be established by which services and electronic advertisements on sites are controlled more finely and more efficiently than in the conventional cases.
Most site use behaviors of users exhibit time factor features. For example, site use tends to decrease on weekends, and there is a phenomenon in which some users use sites actively on a day whose number is a multiple of 5 of the month, while a group of other users uses sites actively on the 1st Monday and last Friday of the month. Further, there is also a tendency for users to refrain from site use late at night of the day. For example, in the field of traffic information services, there has been disclosed a method of calculating a length of travel time required to arrive at a destination, with the degree of traffic congestion on the roads taken into consideration, which changes depending on a time factor such as a day of the week/public holiday/season/day whose number is a multiple of 5 or the like (see, for example, Non-Patent Document 1 below).
(Non-Patent Document 1) Masatoshi KUMAUGAI, Takumi FUSHIKI, Takayoshi YOKOTA, Yutaka SANO, and Kenji SUZUKI, “Development of Long-term Travel Time Forecast Method for Nationwide Traffic Information Services,” Journal of Information Processing Society of Japan, published by Information Processing Society of Japan on Dec. 15, 2004, Volume 45, 12th Issue, pp. 2,696-2,706.
Furthermore, as an example of analyzing a behavior characteristic of a user, there has been disclosed a system and a method in which a behavior of a user is analyzed based on information on a time at which a user's behavior to, for example, browse or purchase merchandise occurs, which has been recorded for each of a plurality of users (for example, JP 2000-285175 A). In this system, the users are classified into segments each constituted of a plurality of users who behave similarly, and an advertisement aimed at users in a target segment is run so as to precede the behavior of the users. However, the above-described conventional system is to analyze behaviors of users by recording time information for each user and therefore is not capable of analyzing, for example, time factor features of behaviors of users who access a site. That is, a time factor feature of a site use status cannot be analyzed quantitatively.